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Dive into the research topics where Marie K. Deserno is active.

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Featured researches published by Marie K. Deserno.


Clinical psychological science | 2015

Mental Disorders as Causal Systems: A Network Approach to Posttraumatic Stress Disorder

Richard J. McNally; Donald J. Robinaugh; Gwyneth W. Y. Wu; Li Wang; Marie K. Deserno; Denny Borsboom

Debates about posttraumatic stress disorder (PTSD) often turn on whether it is a timeless, cross-culturally valid natural phenomenon or a socially constructed idiom of distress. Most clinicians seem to favor the first view, differing only in whether they conceptualize PTSD as a discrete category or the upper end of a dimension of stress responsiveness. Yet both categorical and dimensional construals presuppose that PTSD symptoms are fallible indicators reflective of an underlying, latent variable. This presupposition has governed psychopathology research for decades, but it rests on problematic psychometric premises. In this article, we review an alternative, network perspective for conceptualizing mental disorders as causal systems of interacting symptoms, and we illustrate this perspective via analyses of PTSD symptoms reported by survivors of the Wenchuan earthquake in China. Finally, we foreshadow emerging computational methods that may disclose the causal structure of mental disorders.


Journal of Anxiety Disorders | 2017

A network analysis of DSM-5 posttraumatic stress disorder symptoms and correlates in U.S. military veterans.

Cherie Armour; Eiko I. Fried; Marie K. Deserno; Jack Tsai; Robert H. Pietrzak

OBJECTIVE Recent developments in psychometrics enable the application of network models to analyze psychological disorders, such as PTSD. Instead of understanding symptoms as indicators of an underlying common cause, this approach suggests symptoms co-occur in syndromes due to causal interactions. The current study has two goals: (1) examine the network structure among the 20 DSM-5 PTSD symptoms, and (2) incorporate clinically relevant variables to the network to investigate whether PTSD symptoms exhibit differential relationships with suicidal ideation, depression, anxiety, physical functioning/quality of life (QoL), mental functioning/QoL, age, and sex. METHOD We utilized a nationally representative U.S. military veterans sample; and analyzed the data from a subsample of 221 veterans who reported clinically significant DSM-5 PTSD symptoms. Networks were estimated using state-of-the-art regularized partial correlation models. Data and code are published along with the paper. RESULTS The 20-item DSM-5 PTSD network revealed that symptoms were positively connected within the network. Especially strong connections emerged between nightmares and flashbacks; blame of self or others and negative trauma-related emotions, detachment and restricted affect; and hypervigilance and exaggerated startle response. The most central symptoms were negative trauma-related emotions, flashbacks, detachment, and physiological cue reactivity. Incorporation of clinically relevant covariates into the network revealed paths between self-destructive behavior and suicidal ideation; concentration difficulties and anxiety, depression, and mental QoL; and depression and restricted affect. CONCLUSION These results demonstrate the utility of a network approach in modeling the structure of DSM-5 PTSD symptoms, and suggest differential associations between specific DSM-5 PTSD symptoms and clinical outcomes in trauma survivors. Implications of these results for informing the assessment and treatment of this disorder, are discussed.


Autism | 2017

Multicausal systems ask for multicausal approaches: A network perspective on subjective well-being in individuals with autism spectrum disorder

Marie K. Deserno; Denny Borsboom; Sander Begeer; Hilde M. Geurts

Given the heterogeneity of autism spectrum disorder, an important limitation of much autism spectrum disorder research is that outcome measures are statistically modeled as separate dependent variables. Often, their multivariate structure is either ignored or treated as a nuisance. This study aims to lift this limitation by applying network analysis to explicate the multivariate pattern of risk and success factors for subjective well-being in autism spectrum disorder. We estimated a network structure for 27 potential factors in 2341 individuals with autism spectrum disorder to assess the centrality of specific life domains and their importance for well-being. The data included both self- and proxy-reported information. We identified social satisfaction and societal contribution as the strongest direct paths to subjective well-being. The results suggest that an important contribution to well-being lies in resources that allow the individual to engage in social relations, which influence well-being directly. Factors most important in determining the network’s structure include self-reported IQ, living situation, level of daily activity, and happiness. Number of family members with autism spectrum disorder and openness about one’s diagnosis are least important of all factors for subjective well-being. These types of results can serve as a roadmap for interventions directed at improving the well-being of individuals with autism spectrum disorder.


Scientific Reports | 2018

The role of stabilizing and communicating symptoms given overlapping communities in psychopathology networks

Tessa F. Blanken; Marie K. Deserno; Jonas Dalege; Denny Borsboom; Peter Blanken; Gerard A. Kerkhof; Angélique O. J. Cramer

Network theory, as a theoretical and methodological framework, is energizing many research fields, among which clinical psychology and psychiatry. Fundamental to the network theory of psychopathology is the role of specific symptoms and their interactions. Current statistical tools, however, fail to fully capture this constitutional property. We propose community detection tools as a means to evaluate the complex network structure of psychopathology, free from its original boundaries of distinct disorders. Unique to this approach is that symptoms can belong to multiple communities. Using a large community sample and spanning a broad range of symptoms (Symptom Checklist-90-Revised), we identified 18 communities of interconnected symptoms. The differential role of symptoms within and between communities offers a framework to study the clinical concepts of comorbidity, heterogeneity and hallmark symptoms. Symptoms with many and strong connections within a community, defined as stabilizing symptoms, could be thought of as the core of a community, whereas symptoms that belong to multiple communities, defined as communicating symptoms, facilitate the communication between problem areas. We propose that defining symptoms on their stabilizing and/or communicating role within and across communities accelerates our understanding of these clinical phenomena, central to research and treatment of psychopathology.


Psychological Medicine | 2017

Relating ASD symptoms to well-being: moving across different construct levels

Marie K. Deserno; Denny Borsboom; Sander Begeer; Hilde M. Geurts

BACKGROUND Little is known about the specific factors that contribute to the well-being (WB) of individuals with autism spectrum disorder (ASD). A plausible hypothesis is that ASD symptomatology has a direct negative effect on WB. In the current study, the emerging tools of network analysis allow to explore the functional interdependencies between specific symptoms of ASD and domains of WB in a multivariate framework. We illustrate how studying both higher-order (total score) and lower-order (subscale) representations of ASD symptomatology can clarify the interrelations of factors relevant for domains of WB. METHODS We estimated network structures on three different construct levels for ASD symptomatology, as assessed with the Adult Social Behavior Questionnaire (item, subscale, total score), relating them to daily functioning (DF) and subjective WB in 323 adult individuals with clinically identified ASD (aged 17-70 years). For these networks, we assessed the importance of specific factors in the network structure. RESULTS When focusing on the highest representation level of ASD symptomatology (i.e. a total score), we found a negative connection between ASD symptom severity and domains of WB. However, zooming in on lower representation levels of ASD symptomatology revealed that this connection was mainly funnelled by ASD symptoms related to insistence on sameness and experiencing reduced contact and that those symptom scales, in turn, impact different domains of WB. CONCLUSIONS Zooming in across construct levels of ASD symptom severity into subscales of ASD symptoms can provide us with important insights into how specific domains of ASD symptoms relate to specific domains of DF and WB.


Archive | 2017

Psychologische stoornissen als complexe netwerken

Gabriela Lunansky; Michèle B. Nuijten; Marie K. Deserno; Angélique O. J. Cramer; Denny Borsboom

In dit hoofdstuk wordt een overzicht gegeven van de theorie en de methoden die horen bij het netwerkperspectief. Allereerst wordt stilgestaan bij het latente-variabelenmodel en het verschil met het netwerkperspectief van psychopathologie. De theoretische verschillen tussen beide perspectieven zullen daarbij worden besproken. Daarna wordt de architectuur van netwerken besproken, waarbij wordt ingegaan op wat de entiteiten in het netwerk representeren en hoe ze moeten worden geinterpreteerd. Vervolgens wordt er gekeken naar de laatste bevindingen hoe een psychopathologisch netwerk zich ontwikkelt in de tijd, en bespreken we hoe individuele netwerken geschat kunnen worden. Tot slot worden mogelijk nieuwe behandelstrategieen besproken, door te kijken naar de implicaties van het netwerkperspectief voor de klinische praktijk.


Clinical Neuropsychiatry | 2016

Mental disorders as complex networks : An introduction and overview of a network approach to psychopathology

Michèle B. Nuijten; Marie K. Deserno; Angélique O. J. Cramer; Denny Borsboom


Handbook persoonlijkheidspathologie | 2017

Een symptoom komt nooit alleen : Psychologische stoornissen als complexe netwerken

G. Lunansky; Michèle B. Nuijten; Marie K. Deserno; Angélique O. J. Cramer; Denny Borsboom; E.H.M. Eurelings-Bontekoe; R. Verheul; W.M. Snellem


Clinical Neuropsychiatry | 2016

Mental disorders as complex networks

Michèle B. Nuijten; Marie K. Deserno; Angélique O. J. Cramer; Denny Borsboom


Handboek Persoonlijkheidspathologie | 2017

Psychologische stoornissen als complexe netwerken : Een symptoom komt nooit alleen

G. Lunansky; Michèle B. Nuijten; Marie K. Deserno; Angélique O. J. Cramer; Denny Borsboom; E.H.M. Eurelings-Bontekoe; R. Verheul; W.M. Snellen

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Jonas Dalege

University of Amsterdam

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